Optimizing Bioprocesses Using Functional DOE

By Seongjin Kim, Samsung Biologics

Biopharmaceutical production depends on precisely managing cell culture dynamics to ensure high product quality and process efficiency. Traditional Design of Experiments (DOE) methods are valuable for identifying critical quality attributes (CQAs) and critical process parameters (CPPs) but often focus on static endpoint measurements, overlooking dynamic, time-dependent changes like pH fluctuations or nutrient trends. These variations are critical in optimizing processes, as they significantly impact viable cell density, productivity, and product quality.

Functional DOE addresses this gap by analyzing continuous changes across a range of conditions, complementing traditional methods to provide a more comprehensive understanding of complex biological systems. For example, it captures dynamic interactions in pH, osmolality, pCO2 control, and glucose metabolism, which traditional DOE might miss. By integrating Functional DOE with traditional approaches, manufacturers gain a deeper insight into multifactorial processes, improving experimental design, optimizing production parameters, and achieving consistent results.

This combined methodology enhances decision-making and process optimization by leveraging both endpoint and time-series data. The result is a robust framework that aligns process control with quality goals, enabling better protein therapeutic development, higher yields, and greater operational efficiency. This dual approach represents a significant advancement in the biopharmaceutical industry's ability to manage complex production challenges.